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OverviewThe Applied Intelligence Data Engineering team is seeking a Senior Software Engineer - Cloud Infrastructure. This is a hybrid role that blends deep software engineering with hands-on ownership of cloud infrastructure. It is purpose-built for engineers who are equally writing production Java services and designing multi-cloud platform architecture.
In this role, you will own the full lifecycle of cloud-native systems. You will build high-performance streaming applications and architect the infrastructure they run on. You will also ensure both are production-grade, observable, and secure. You will bridge application and platform engineering, reducing the gap between what software teams need and what the cloud platform delivers.
This role requires deep expertise in distributed systems, cloud-native architecture, Kubernetes, and software engineering best practices. You should have a track record of operating at both the application and infrastructure layers.
Key ResponsibilitiesOptimize Data Streaming Applications on Cloud
- Own end-to-end performance of data streaming applications running on cloud infrastructure - from Kafka topic configuration through consumer processing and downstream delivery.
- Profile and tune streaming pipelines to maximize throughput and minimize latency, leveraging cloud-native compute, storage, and networking resources.
- Identify and address bottlenecks at the intersection of application code and cloud resource constraints, including CPU throttling, network saturation, I/O limits, and memory constraints.
- Design and implement cloud resource utilization strategies. This includes spot/preemptible instances, managed streaming services, and dynamic node pool scaling to balance performance with cost efficiency.
- Benchmark streaming pipelines end-to-end and translate findings into actionable infrastructure and code improvements.
- Collaborate with Data and AI/ML engineering teams to ensure streaming pipelines are optimally provisioned for real-time feature engineering, inference, and analytics workloads.
Design & Build Cloud-Native Applications
- Develop high-throughput, low-latency streaming applications using Java and Kafka.
- Design event-driven microservices that process, enrich, and route real-time data at scale.
- Implement reactive, non-blocking architectures to support high concurrency and resilience.
- Develop reusable streaming frameworks, libraries, and platform capabilities to improve engineering velocity and standardization.
Architect & Operate Multi-Cloud Infrastructure
- Architect, implement, and optimize multi-cloud infrastructure across Google Cloud Platform and OCI to support large-scale data and streaming workloads.
- Design and implement advanced networking architectures, including VPC peering, VPNs, load balancers, and cross-region failover strategies.
- Build and maintain Terraform-based infrastructure-as-code frameworks to standardize deployments and enable developer self-service.
- Define autoscaling, deployment, failover, and resource optimization strategies for high-volume production systems.
- Contribute to platform-wide architecture decisions related to scalability, resiliency, high availability, and disaster recovery.
Kubernetes & Container Engineering
- Deploy and manage containerized microservices within Kubernetes environments (GKE, OKE) across cloud platforms.
- Implement container orchestration best practices, service-mesh configurations, and rolling-deployment strategies.
- Partner with platform engineering teams to improve developer tooling, deployment automation, and runtime reliability.
Production Reliability & Performance
- Ensure production-grade reliability, observability, and operational maturity across streaming platforms and infrastructure.
- Implement comprehensive observability using Prometheus, Grafana, centralized logging, distributed tracing, and health monitoring.
- Optimize systems for throughput, latency, resiliency, resource efficiency, and cloud cost governance.
- Build automated testing strategies for streaming and infrastructure workflows, including unit, integration, contract, chaos, and performance testing.
- Lead incident response, root-cause analysis, and postmortems to improve uptime and reduce operational risk.
Cross-Functional Collaboration
- Partner with Data Engineering teams to integrate streaming architectures with batch processing, data lakes, and analytical platforms.
- Collaborate with Software Engineering, Product Management, and API teams to enable real-time services and data-driven applications.
- Work closely with AI/ML engineering teams to support real-time feature engineering, inference pipelines, and operational AI workload.
- Clearly communicate technical tradeoffs to engineering stakeholders. Also, discuss scalability considerations and operational risks.
Technical Management
- Lead architectural discussions, design reviews, and technical deep dives across distributed systems and cloud infrastructure.
- Drive engineering standards across code quality, documentation, observability, security, and platform maintainability.
- Influence long-term technical strategy and modernization initiatives for real-time data infrastructure and cloud platforms.
Required Technical SkillsStreaming Optimization & Cloud Resource Utilization
- Deep expertise in optimizing data streaming applications for throughput, latency, and cost-efficiency across cloud environments.
- Proficient in tuning Kafka producers, consumers, and brokers - including batch sizing, compression, partition strategies, and consumer lag management - within cloud-hosted deployments.
- Experience leveraging cloud-native managed services (e.g., Kafka, Google Cloud Platform Pub/Sub, BigQuery Streaming; OCI Streaming) to complement or extend Kafka-based pipelines.
- Skilled at right-sizing and dynamically allocating cloud compute resources (VMs, node pools, spot/preemptible instances) to match streaming workload profiles and reduce infrastructure spend.
- Familiarity with cloud-native autoscaling patterns for streaming consumers, including KEDA, HPA, and custom metrics-based scaling in Kubernetes.
- Ability to identify and address performance bottlenecks at the intersection of application code and cloud resource limits
- You should have experience benchmarking and profiling streaming pipelines from start to finish. You also need to turn your findings into improvements for infrastructure and code.
Basic QualificationsThis is a hybrid role. Candidates must have hands-on experience in both software engineering and cloud infrastructure.
- 7+ years of experience in software engineering and cloud infrastructure, with at least 3+ years in each area.
- Demonstrated expertise in optimizing data streaming applications on cloud infrastructure.
- Proven track record building and operating production-grade real-time data platforms.
- Experience mentoring engineers and collaborating across teams.
- Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.
#LI-PV1
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ADDITIONAL INFORMATION
Hiring Salary Range: $124,000.00 - 186,000.00.
The hiring salary range for this position applies to New York, California, Colorado, Washington state, and most other geographies. Starting pay for the successful applicant depends on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education. The benefits available for this position include medical, dental, vision, 401(k) plan, life insurance coverage, disability benefits, tuition assistance program and PTO or, if applicable, as otherwise dictated by the appropriate Collective Bargaining Agreement. This position is bonus eligible.
What We Offer:- Attractive compensation and comprehensive benefits packages. Check out our full list of benefits here: ;/li>
- Generous paid time off.
- An exciting and fulfilling opportunity to be part of one of Paramount's most dynamic teams.
- Opportunities for both on-site and virtual engagement events.
- Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.
- Explore life at Paramount: ;/li>
Paramount is an equal opportunity employer (EOE) including disability/vet.
At Paramount, the spirit of inclusion feeds into everything that we do, on-screen and off. From the programming and movies we create to employee benefits/programs and social impact outreach initiatives, we believe that opportunity, access, resources and rewards should be available to and for the benefit of all. Paramount is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, and Veteran status.
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